PHD Project - Driver energy prediction
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"# Datensatz herunterladen\n",
"\n",
"`SETUP_ID` anpassen, Rest läuft automatisch.\n",
"\n",
"Einige Datensätze besitzen keinen Eintrag für `flt_obd_speed`. Für eine Liste der Datensätze *mit* diesem Wert kann beispielsweise folgende SQL-Abfrage verwendet werden (Achtung, braucht (prinzipbedingt) sehr lange!):\n",
"\n",
"```sql\n",
"select setup_id s, count(*) n\n",
"from computeddata\n",
"group by s\n",
"having not exists (\n",
" select *\n",
" from computeddata\n",
" where setup_id = s\n",
" and flt_obd_speed is null)\n",
"order by n asc\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "bd18001b",
"metadata": {},
"outputs": [],
"source": [
"SETUP_ID = 868\n",
"import csv\n",
"from runsql import runsql\n",
"\n",
"reader = runsql('select distinct setup_id from computeddata')\n",
"reader_data = list(reader) # list(...) so that following cells can be repeated"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "dfcd912a",
"metadata": {},
"outputs": [],
"source": [
"ids = []\n",
"for i in reader_data:\n",
" ids.append(int(i['setup_id']))"
]
},
{
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"execution_count": 20,
"id": "1f8c5b69",
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{
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"1122"
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],
"source": [
"len(ids)"
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